The broad objective of the Resource is to apply advanced methods in Computer Science, particularly in Artificial Intelligence (AI), to biomedical problems. The Resource will promote the development and use of computer systems for intelligent consultation in medical diagnosis and therapy and for research assistance in processes of scientific experimentation and theory formation. The organization of knowledge in a domain, both formal and judgmental (obtained from experts), and its representation in computers, is of central importance in the Resource. Knowledge-based systems that rely on models, heuristic rules, and other representations that facilitate the use of knowledge in varius reasoning tasks, will be developed and studied. The Resource has three major areas of study: Area 1 - Medical Modeling and Decision-Making in several medical domains with emphasis on rheumatology and ophthalmology; Area 2 - Modeling of Belief Systems and Common Sense Reasoning with emphasis on the psychology of action interpretation; and Area 3 - Artificial Intelligence studies with emphasis on Representations, Reasoning and System Development problems of relevance to the Resource objectives. The Resource continues to sponsor the national Artificial Intelliquence in Medicine (AIM) Workshops. Next year, The Resource will collaborate with the SUMEX-AIM project at Stanford to arrange the Workshop on the West Coast. After its enhancement last year, the RUTGERS/LCSR computer is serving as a shared resource, in coordination with the SUMEX-AIM facility, for the national AIM community. Our research is interdisciplinary and interinstitutional. The studies in Medical Modeling and Decision-Making are performed jointly by computer and medical scientists at Rutgers and elsewhere in the country and abroad. Work on a rheumatology consultant is developing in the context of a close collaboration with investigators in the Univ. of Missouri and in other institutions. Work in glaucoma and in neurophysiology is continuing in collaborations with ONET (Ophthalmologial Network) investigators in Washington Univ. and other institutions. The AIM computer network supports these collaborations. Methods are developed for transferring design concepts and specific systems that grow in research environments into clinical prototypes that run on small machines.